Hope this could be helpful for everybody else. Starting development server at Quit the server with CONTROL-C.įinal state of the code lines was the following : from rest_framework import serializersĬlass CampaignsProductsSerializers(srlz.DynamicFieldsModelSerializer): System check identified no issues (0 silenced).ĭjango version 2.0.7, using settings 'settings_development_mlazo' project/settings/manage.py runserver 0:8002 -settings=settings_development_mlazo Therefore, django runserver was executed without problems. Obj.product, fields=p_fields, many=False, # and create the following method and call from there the required serializer class Product = serializers.SerializerMethodField() Additionally, the optimal data types are inferred and applied, which also increases memory efficiency. This is achieved by dropping empty and single valued columns as well as empty and duplicate rows (neither found in this example). So, as mentioned by the lines above how to solve it ( top-level import ), I proceed to do the following changes : # change By applying klib.datacleaning () the size reduces by about 44 MB (-85.2). Product = srlzprod.ProductsSerializers(fields=,read_only=True,) Promotion_description = serializers.SerializerMethodField() If you say make server (and the makefile problem for the all target is fixed), then the mpasswdsort program will be relinked from the two object files each time you run make server, because the rules for the server target do not create a file called server. What I wanted to accomplished was the following : class CampaignsProductsSerializers(srlz.DynamicFieldsModelSerializer):īank_name = serializers.CharField(trim_whitespace=True,)Ĭoupon_type = serializers.SerializerMethodField() ModuleNotFoundError: No module named 'product' I was getting a problem like this : from product import serializers as srlzprod # the line below was the problem 'srlzprod'įrom products import serializers as srlzprod This time my problem was importing Serializers ( django and restframework ) from different modules such as the following : from rest_framework import serializers Firstly, we can identify columns where all or most of the values are missing. I have crossed with this issue many times, but I didnt try to dig deeper about it. A quick way to achieve that is to use the missing value visualization of klib, which can be called as easy as follows: This single plot already shows us a number of important things.
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